no code implementations • 7 May 2024 • Beng Chin Ooi, Shaofeng Cai, Gang Chen, Kian Lee Tan, Yuncheng Wu, Xiaokui Xiao, Naili Xing, Cong Yue, Lingze Zeng, Meihui Zhang, Zhanhao Zhao
In the wake of rapid advancements in artificial intelligence (AI), we stand on the brink of a transformative leap in data systems.
no code implementations • 1 May 2024 • Lingze Zeng, Naili Xing, Shaofeng Cai, Gang Chen, Beng Chin Ooi, Jian Pei, Yuncheng Wu
This SQL-aware MoE technique scales up the modeling capacity, enhances effectiveness, and preserves efficiency by activating only necessary experts via the gating network during inference.
no code implementations • 15 Apr 2024 • Jiaqi Zhu, Shaofeng Cai, Fang Deng, Junran Wu
However, existing approaches depend on static anomaly prompts that are prone to cross-semantic ambiguity, and prioritize global image-level representations over crucial local pixel-level image-to-text alignment that is necessary for accurate anomaly localization.
no code implementations • 15 Mar 2024 • Naili Xing, Shaofeng Cai, Zhaojing Luo, Beng Chin Ooi, Jian Pei
This transition demands an efficient and responsive anytime NAS approach that is capable of returning current optimal architectures within any given time budget while progressively enhancing architecture quality with increased budget allocation.
no code implementations • 28 Dec 2023 • Jiaqi Zhu, Shaofeng Cai, Fang Deng, Beng Chin Ooi, Wenqiao Zhang
Real-time analytics and decision-making require online anomaly detection (OAD) to handle drifts in data streams efficiently and effectively.
no code implementations • ICLR 2022 • Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low
Recent years have witnessed a surging interest in Neural Architecture Search (NAS).
1 code implementation • 5 Jul 2021 • Shaofeng Cai, Kaiping Zheng, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Meihui Zhang
The key idea is to model feature interactions with cross features selectively and dynamically, by first transforming the input features into exponential space, and then determining the interaction order and interaction weights adaptively for each cross feature.
no code implementations • 14 Aug 2020 • Yuncheng Wu, Shaofeng Cai, Xiaokui Xiao, Gang Chen, Beng Chin Ooi
Federated learning (FL) is an emerging paradigm that enables multiple organizations to jointly train a model without revealing their private data to each other.
no code implementations • 24 Mar 2020 • Kaiping Zheng, Shaofeng Cai, Horng Ruey Chua, Wei Wang, Kee Yuan Ngiam, Beng Chin Ooi
In high stakes applications such as healthcare and finance analytics, the interpretability of predictive models is required and necessary for domain practitioners to trust the predictions.
no code implementations • 16 Mar 2020 • Chengxin Wang, Shaofeng Cai, Gary Tan
Predicting the future paths of an agent's neighbors accurately and in a timely manner is central to the autonomous applications for collision avoidance.
no code implementations • ICLR 2020 • Shaofeng Cai, Yao Shu, Wei Wang, Gang Chen, Beng Chin Ooi
Recent years have witnessed growing interests in designing efficient neural networks and neural architecture search (NAS).
1 code implementation • ICLR 2020 • Yao Shu, Wei Wang, Shaofeng Cai
Neural architecture search (NAS) searches architectures automatically for given tasks, e. g., image classification and language modeling.
no code implementations • 6 Sep 2019 • Dumitrel Loghin, Shaofeng Cai, Gang Chen, Tien Tuan Anh Dinh, Feiyi Fan, Qian Lin, Janice Ng, Beng Chin Ooi, Xutao Sun, Quang-Trung Ta, Wei Wang, Xiaokui Xiao, Yang Yang, Meihui Zhang, Zhonghua Zhang
With 5G on the verge of being adopted as the next mobile network, there is a need to analyze its impact on the landscape of computing and data management.
Networking and Internet Architecture Databases Distributed, Parallel, and Cluster Computing
no code implementations • 13 May 2019 • Shaofeng Cai, Yao Shu, Wei Wang, Beng Chin Ooi
The deployment of deep neural networks in real-world applications is mostly restricted by their high inference costs.
no code implementations • 6 Apr 2019 • Shaofeng Cai, Yao Shu, Gang Chen, Beng Chin Ooi, Wei Wang, Meihui Zhang
However, many recent works show that the standard dropout is ineffective or even detrimental to the training of CNNs.
1 code implementation • 3 Apr 2019 • Shaofeng Cai, Gang Chen, Beng Chin Ooi, Jinyang Gao
Model slicing could be viewed as an elastic computation solution without requiring more computational resources.